Configurable computing machines have emerged as a technology capable of providing high computational performance on a diversity of applications, including 1-D and 2-D signal processing, image processing, simulation acceleration, and scientific computing. In many cases, applications solved with configurable computing techniques supplant the equivalent of tens or hundreds of contemporary microprocessors or digital signal processors (DSPs). High performance is achieved by (dynamically) building custom computational operators, pathways, and pipelines suited to specific properties of the task at hand. With this approach, characteristics of a particular application, such as parallelism, locality, and data resolution can be fully exploited. Hence, configurable computing machines provide the computational performance benefits of application-specific integrated circuits (ASICs), yet retain the flexibility and rapid reconfigurability of general purpose microprocessors.